Nonparametric Tests for Serial Independence Based on Quadratic Forms

  title={Nonparametric Tests for Serial Independence Based on Quadratic Forms},
  author={Cees Diks and Valentyn Panchenko},
Tests for serial independence and goodness-of-fit based on divergence notions between probability distributions, such as the Kullback-Leibler divergence or Hellinger distance, have recently received much interest in time series analysis. The aim of this paper is to introduce tests for serial independence using kernel-based quadratic forms. This separates the problem of consistently estimating the divergence measure from that of consistently estimating the underlying joint densities, the… CONTINUE READING

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